• International Journal of Contents
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• v.1 no.2
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• pp.39-43
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• 2005

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.271-286
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• 2006

In this paper, we introduce automatic question generation technique using the language resources like User-Word Intelligent Network(U-WIN) and Korean dictionary including quite a for of information. And we present Korean word learning system with this technique. The item pool method which almost learning-system are using makes some problems. As a solution of the problems, we classified into 8 question type and implemented the Korean word learning system which is making the Korean question automatically by using the morphological and semantic information according to the automatic question generation pattern of each type.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.27-36
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• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• Journal of Korean Medical classics
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• v.22 no.4
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• pp.189-198
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• 2009

Considering the opinions of annotators, the remedy about excess of east and deficiency of west from "the seventy-fifth question" can be arranged as follows. "The seventy-fifth question", with "the sixty-ninth question", explains excess and deficiency of mother and son. Abatement of fire and invigoration of water[瀉火補水] in the excess of wood and deficiency of metal[木實金虛] presents a remedy, which has been applied in herbs and medicine application henceforth. "The seventy-fifth question" is a unique theory from " Nan-gyeong(難經)", and does not continue the theory of "Hwangjenaegyeong(黃帝內經)". "The seventy-fifth question" mentions the relationship of excess and deficiency of the five elements and five viscera, but does not mention excess and deficiency of invigoration and abatement of the meridian. Remedy from abatement of fire and invigoration of water[瀉火補水] in the excess of wood and deficiency of metal[木實金虛] is an abnormal, temporary and extraordinary method. This remedy is applied in Saam acupuncture[舍巖鍼] as A-variation form. The process where Son allows excess of mother[子能令母實] and mother allows deficiency of son[母能令子虛] in the abatement of fire and invigoration of water[瀉火補水] is a mechanism, not a remedy. Generation after generation, medical practitioners can be classified into those that claimed abatement of fire and invigoration of water[瀉火補水] because of the relation with excess of liver and deficiency of lung[肝實肺虛], abatement of heart(瀉心) due to the excess of liver(肝實), or invigoration of Eum and abatement of Yang[補陰瀉陽].

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2718-2731
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• 2023

This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.285-291
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• 2001

This paper describes a natural language question answering system that can be used by students in getting as solution to their queries. Unlike AI question answering system that focus on the generation of new answers, the present system retrieves existing ones from question-answer files. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, it uses a semantic knowledge base (WordNet) to improve its ability to match question. Paper describes the design and the current implementation of the system as an intelligent tutoring system. Main drawback of the existing tutoring systems is that the computer poses a question to the students and guides them in reaching the solution to the problem. In the present approach, a student asks any question related to the topic and gets a suitable reply. Based on his query, he can either get a direct answer to his question or a set of questions (to a maximum of 3 or 4) which bear the greatest resemblance to the user input. We further analyze-application fields for such kind of a system and discuss the scope for future research in this area.

• The Journal of Korean Association of Computer Education
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• v.5 no.2
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• pp.49-59
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• 2002

There have been many attempts to educationally utilize a computer. As a result, a number of learning programs and testing programs have been developed. Testing programs developed so far are rather focusing on giving learners questions without interactivity. Question givers also have to feed question data into a computer. Therefore, this thesis, firstly, explains how learners themselves feed question data into a computer. Secondly, this thesis explains how to develop such a system that can produce new questions based on the question data fed by learners. This paper also introduces the system environment, which features the test item generation system, and explains the system environment by exemplifying internal modules, a test item bank. Besides, we also describe how to apply this system to educational programs and identify whether it is possible to apply it to a Chinese subject and others.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.144-147
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• 2015

Question Answering (QA) services can provide exact answers to user questions written in natural language form. This research focuses on how to build a QA system for a specific domain area. Online and offline QA system architecture of targeted domain such as domain detection, question analysis, reasoning, information retrieval, filtering, answer extraction, re-ranking, and answer generation, as well as data preparation are presented herein. Test results with an official Frequently Asked Question (FAQ) set showed 68% accuracy of the top 1 and 77% accuracy of the top 5. The contribution of each part such as question analysis system, document search engine, knowledge graph engine and re-ranking module for achieving the final answer are also presented.

• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.84-92
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• 2007

The purpose of this study was to investigate biologists' brain activation patterns during the generation of scientific questions on biological phenomena. Eight right-handed healthy biologists volunteered to be participants in the present study. The question-generation tasks were presented in a block design. The BOLD signals of the biologists' brain were measured by 3.0T fMRI system and data were analyzed using Statistical Parametric Mapping (SPM2). According to our results, the left inferior and middle frontal gyri, the medial prefrontal cortex, the bilateral hippocampus, the occipito-parietal route, the fusiform gyrus, and the cerebellum were activated significantly during the generation of scientific questions. Therefore, we suggested that generating scientific question is associated with analyzing observed situations, using verbal strategy, retrieving episodic memories for comparisons, and feeling cognitive conflicts.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.173-179
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• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.